OBJECTIVES: Pharmacogenetic (PG) algorithms of warfarin dosing have been proposed as potential improvement of anticoagulation control. Despite several randomized clinical trials, the clinical benefit was not consistently proven. The objective of this study was to estimate the opportunity cost of introduction of warfarin PG testing into health system using an expected value of perfect information (EVPI) approach. METHODS: Previously developed cost-effectiveness model was employed to evaluate the PG algorithm-based warfarin dosing versus standard treatment. Differences in anticoagulation control, in terms of percentage of time in therapeutic range (TTR), were used to simulate thromboembolic and haemorrhagic events. The outcomes were valued in quality-adjusted life-years (QALY) and 2014 cost. Uncertainty in the model parameters was assessed using probabilistic sensitivity analysis and EVPI was estimated at a threshold of 25,000 EUR/QALY gained. RESULTS: In the base case, where price of PG test was 40 EUR, the ICER of genotype-guided treatment was 8.146 EUR/QALYg compared to the standard treatment. When uncertainty about clinical efficacy was examined, ICER ranged from approximately 1.000 EUR/QALYg to dominated strategy. Another important factor was the price of PG test. In the base case, the treatment using PG algorithm had highest expected net-benefit with opportunity loss surrounding uncertainty about clinical efficacy of 2.9 EUR per treated patient. Conversely, increasing the cost of PG test by 3 times, to 120 EUR, resulted in the highest total expected net-benefit for standard treatment. Selecting the genotype-guided treatment instead of standard therapy would result in opportunity loss of 47.2 EUR, while EVPPI for standard treatment was 0.82 EUR. CONCLUSIONS: The price of PG test is an important factor about decision of warfarin PG introduction into health system or investment into additional clinical trials. The smaller cost of PG test means lower opportunity cost, consequentially future research should not have important impact on economic aspect of decision.